Hunting behavior of a solitary sailfish Istiophorus platypterus and estimated energy gain after prey capture

Foraging behavior and interaction with prey is an integral component of the ecological niche of predators but is inherently difficult to observe for highly mobile animals in the marine environment. Billfishes have been described as energy speculators, expending a large amount of energy foraging, expecting to offset high costs with periodic high energetic gain. Surface-based group feeding of sailfish, Istiophorus platypterus, is commonly observed, yet sailfish are believed to be largely solitary roaming predators with high metabolic requirements, suggesting that individual foraging also represents a major component of predator–prey interactions. Here, we use biologging data and video to examine daily activity levels and foraging behavior, estimate metabolic costs, and document a solitary predation event for a 40 kg sailfish. We estimate a median active metabolic rate of 218.9 ± 70.5 mgO2 kg−1 h−1 which increased to 518.8 ± 586.3 mgO2 kg−1 h−1 during prey pursuit. Assuming a successful predation, we estimate a daily net energy gain of 2.4 MJ (5.1 MJ acquired, 2.7 MJ expended), supporting the energy speculator model. While group hunting may be a common activity used by sailfish to acquire energy, our calculations indicate that opportunistic individual foraging events offer a net energy return that contributes to the fitness of these highly mobile predators.

. Completed biologging tag package in 90 L Loligo swim tunnel, and associated linear regression of swim speed calibration.
While this calibration step in the flume was necessary, these are ideal conditions and may not be representative of the situation once it is attached to a fish. To ensure that the speed sensor in the flume accurately represents the velocity once it is attached to a fish, we compared the speed measured by the impeller to another established method of calculating speed via the vertical velocity of the fish (ms -1 ) and the body pitch angle derived from the accelerometer, using body pitch angles of > 20° [1,2]. We regressed the vertical velocity (m/s) and body pitch angle method against the speed measured by the impeller attached to the tag. The blue line is the linear regression of the two, and the black line represents a 1:1 relationship. In general, the tag speed sensor matches the calculated speed method with some variability (p < 0.001, r 2 = 0.7, y =1.03x -0.02). The advantage of using the impeller is we are still able to obtain a speed measurement at low body pitch angles or at times when the fish is at a constant depth. Figure S2. Linear regression (blue line) of the speed measured by the animal-borne impeller (Measured Speed (m/s)) and the calculated speed using the equation speed (m/s) = vertical velocity (m/s) / sin(φ), where φ is the body pitch. p < 0.001, r 2 = 0.7, y =1.03x -0.02. The black line represents a 1:1 relationship.
Finally, while there is little doubt that the tag had some effect on the drag of the sailfish, in the absence of swim tunnel experiments with and without a tag, we cannot say with certainty exactly how much, and how this may have affected the sailfish's behavior. However, using cross-sectional area measurements from the largest section of a similarly sized sailfish (just posterior to the head; where the tag was placed) [3] we calculated the drag acting on a body of that area using the equation FD = 0.5CρAν 2 , where C is the drag coefficient (0.24 [unitless]) [3], ρ is the density of seawater at 27°C [1023 kg m -3 ], A is the area of the object (cross-sectional area; 0.025 m 2 ), and ν is the velocity of the object (1 m/s). This resulted in a drag of 3.1 N acting on the sailfish. Because the tag was designed to be as hydrodynamic as possible, it is narrower at the leading edge (facing in the direction of travel) and gets thicker at the trailing edge (seen in figure 1 and figure S1). Using the cross-sectional area from the narrow end of the tag (0.001 m 2 ) and a drag coefficient of 0.6, we calculated an added drag of 0.3 N, or 9% of the drag on the sailfish. Using the largest portion of the tag for the cross-sectional area (0.0026 m 2 ), we calculated a drag of 0.79 N, or roughly 25% of the drag acting on the sailfish. While we cannot say exactly how this may have impacted behavior in the absence of behavioral data without a tag, Sagong et al. (2013) found that there was a 21.5% increase in the drag when they attached pectoral fins to their specimens. As such, a 9-25% increase from the tag does not appear to be a major increase, but there is undoubtedly some effect of tag attachment which may lead to an underestimation of metabolic rate estimates.

Proxy Species Selection & Metabolic Rate Calculation
Obtaining direct measurements of oxygen consumption at varying mass, swim speeds and activity levels is not currently feasible for sailfish. However, recent studies indicate that lifestyle, trophic level, and morphology are correlated with metabolic rate such that pelagic, upper trophic level fishes with similar morphology (e.g. high caudal fin aspect ratio, gill surface area) exhibit similar and elevated metabolic rates [4][5][6][7]. As such, sailfish may have metabolic demands comparable to dolphinfish [Coryphaena hippurus; 8], another subtropical epipelagic predator with comparable ecological interactions [9]. Additionally, the gill surface area to body mass ratio is very similar between dolphinfish and the closely related striped marlin (Kajikia audax) [12], indicating similar oxygen uptake capabilities between dolphinfish and istiophorid billfishes regardless of body size, further suggesting dolphinfish provide a suitable proxy for sailfish metabolic rate. Although sailfish possess cranial endothermy and warm their brain and retina with a specialized thermogenic organ that sits beneath the brain, the rest of the body is ectothermic and does not retain metabolic heat [10]. Therefore, we did not feel that a subtropical scombrid with endothermy, such as yellowfin tuna (Thunnus albacares), which warm their muscle, viscera and brain via vascular counter-current heat exchangers, were an acceptable proxy species for this study [11]. Although dolphinfish are smaller than the sailfish tagged in the present study, the effects of body size on swimming metabolic rates in fishes can be removed by using swim speed relative to body length [13]. More specifically, log swimming metabolic rates plotted against swim speed relative to body length produce similar straight lines independent of body size of the fish [13]. Owing to the lack of direct measurements of swimming metabolic rates for larger fishes with regional endothermy, data for dolphinfish was regarded as the best available information. Therefore, we took the equation of the line (y = 0.1168x 2 -0.6457x + 1.1994) used to describe the relationship between the cost of transport (mgO2 kg -1 m -1 ) and swim speed (U; BL s -1 ) of dolphinfish in the control group (no oil exposure) of [14] . We then converted cost of transport to mass-specific oxygen consumption (ṀO2, mgO2 kg -1 h -1 ) by multiplying by both the mean fork length of dolphinfish in the control group (0.291 m) and 3600 s. Oxygen consumption (MO2; mgO2 kg -1 h -1 ) at various swim speeds was estimated using the equation log(MO2) = [cU + log(d)], where c and d are the slope and intercept of the logarithmic regression, and U is the swim speed (BLs -1 ) after correcting for the BL of the sailfish ( Figure   S3). By correcting for the body length of the sailfish, the range of BLs -1 for the sailfish spans 0.08-0.63 BLs -1 , accounting for the majority of our observed speed data, and we linearly extrapolate to higher swim speeds ( Figure S3). MO2 was calculated continuously for every speed measurement throughout the 24 hours from the sailfish tag data, and we then took the inverse log of MO2 and corrected for mass of the dolphinfish (MD) in [14] to obtain VO2 (mgO2 h -1 ). Oxygen consumption for the 40 kg sailfish was then calculated using the equation: where AMRE is the estimated active metabolic rate (mgO2 h -1 ), VO2 is the oxygen consumption at each swim speed (mgO2 h -1 ), b is the mass scaling exponent, and MS is the sailfish mass (kg).
We corrected AMRE for temperature by multiplying by Q10^((T2-T1)/10) [16], where Q10 is the increase in standard metabolism with an increase in 10°C, T1 is the temperature the dolphinfish were tested at in [14], and T2 was the continuous temperature experienced by the sailfish, with Q10 set to 1.83 [5,15]. AMRE was then made mass-specific to the estimated mass of the sailfish and corrected to units of mgO2 kg -1 h -1 .

Energy Expenditure and Prey Consumption
To estimate the amount of energy expended over the course of the 24-h period and during the predation event, we first converted the AMRE from mgO2 kg -1 h -1 to kJ kg -1 h -1 by multiplying by the oxy caloric coefficient of 0.013 kJ mgO2 -1 . Because we sum across seconds, we then divide this by 3600 leaving kJ kg -1 sec -1 , and finally multiplied by the estimated mass of the sailfish (40 kg), leaving an estimate of kJ burned sec -1 for the sailfish. Each value of kJ sec -1 was then summed across each period (the entire day or just the predation event;   iterations when calculating the estimated active metabolic rate (AMRE) of the sailfish. Figure S5. Output of the log transformed estimated active metabolic rate (AMRE; mgO2 kg -1 h -1 ) from the 10,000 iterations over the 24 h period. AMRE was calculated as the median of the 10,000 samples (solid red line), with the interquartile range (25 -75%) taken to represent a range of probable AMRE values (dotted red lines).